Spark (PySpark) to extract from SQL Server

[#1]

Use Apache Spark to connect to SQL Server, extract a table from SQL Server, and load the extracted rows into a Hive table:

• You will need to download JDBC driver for SQL Server
• Download the driver from: https://www.microsoft.com/en-us/download/details.aspx?id=11774
• Run code: /usr/bin/spark-submit --driver-class-path /home/centos/sqljdbc_4.0/enu/sqljdbc4.jar --master yarn-client my_script.py

import os
from pyspark import SparkConf,SparkContext
from pyspark.sql import HiveContext

conf = (SparkConf()
  .setAppName("data_import")
  .set("spark.dynamicAllocation.enabled","true")
  .set("spark.shuffle.service.enabled","true"))
sc = SparkContext(conf = conf)

sqlctx = HiveContext(sc)

df = sqlctx.load(
  source="jdbc",
url="jdbc:sqlserver://ec2-54-244-44-6.us-west-2.compute.amazonaws.com:1433;database=sales;user=my_username;password=my_password",
dbtable="orders")


## this is how to write to an ORC file
df.write.format("orc").save("/tmp/orc_query_output")

## this is how to write to a hive table
df.write.mode('overwrite').format('orc').saveAsTable("test_table")

[#2]

I am using pyspark3 on Spark 2.02 and when run the above code i get following error:

'HiveContext' object has no attribute 'load'
Traceback (most recent call last):
AttributeError: 'HiveContext' object has no attribute 'load'

[#3]

I tested the above code with Spark 1.6.2. I have not tested with Spark 2.0.

I see your using Spark 2.0. Spark 2.0 uses the SparkSession which replaces both HiveContext and SQLContext. You will have to use SparkSession. See below. After creating the SparkSession, like how I do below, I don't know off hand if the following will work: 'spark.load( source="jdbc", url="jdbc:sqlserver://ec2-54-244-44-6.us-west-2.compute.amazonaws.com:1433;database=sales;user=my_username;password=my_password", dbtable="orders")'

from pyspark.sql import SparkSession

spark = SparkSession \

.builder \

.appName("my_application_name") \

.config("spark.shuffle.service.enabled","true") \

.config("spark.dynamicAllocation.enabled","true") \

.getOrCreate()

[#4]

Hey i am getting the following error

17/05/05 17:19:20 ERROR DefaultWriterContainer: Job job_201705051719_0000 aborted.
Traceback (most recent call last):
  File "/opt/sqlscrapper.py", line 24, in <module>
    df.write.format("orc").save("/tmp/orc_query_output")
  File "/usr/hdp/2.5.3.0-37/spark/python/lib/pyspark.zip/pyspark/sql/readwriter.py", line 397, in save
  File "/usr/hdp/2.5.3.0-37/spark/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py", line 813, in __call__
  File "/usr/hdp/2.5.3.0-37/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 45, in deco
  File "/usr/hdp/2.5.3.0-37/spark/python/lib/py4j-0.9-src.zip/py4j/protocol.py", line 308, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o51.save.
: org.apache.spark.SparkException: Job aborted.
        at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1.apply$mcV$sp(InsertIntoHadoopFsRelation.scala:154)
        at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1.apply(InsertIntoHadoopFsRelation.scala:106)
        at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1.apply(InsertIntoHadoopFsRelation.scala:106)
        at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:56)
        at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation.run(InsertIntoHadoopFsRelation.scala:106)
        at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:58)
        at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:56)
        at org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:70)
        at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132)
        at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
        at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:130)
        at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:55)
        at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:55)
        at org.apache.spark.sql.execution.datasources.ResolvedDataSource$.apply(ResolvedDataSource.scala:256)
        at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:148)
        at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:139)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
        at java.lang.reflect.Method.invoke(Method.java:498)
        at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
        at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
        at py4j.Gateway.invoke(Gateway.java:259)
        at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
        at py4j.commands.CallCommand.execute(CallCommand.java:79)
        at py4j.GatewayConnection.run(GatewayConnection.java:209)
        at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3, db-hdp-dn2.darbeirut.com): java.lang.ClassNotFoundException: com.microsoft.sqlserver.jdbc.SQLServerDriver
        at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
        at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
        at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
        at org.apache.spark.sql.execution.datasources.jdbc.DriverRegistry$.register(DriverRegistry.scala:38)
        at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$2.apply(JdbcUtils.scala:53)
        at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$2.apply(JdbcUtils.scala:52)
        at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$$anon$1.<init>(JDBCRDD.scala:347)
        at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD.compute(JDBCRDD.scala:339)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:313)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:277)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
        at org.apache.spark.scheduler.Task.run(Task.scala:89)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)


Driver stacktrace:
        at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1433)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1421)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1420)
        at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
        at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1420)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:801)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:801)

[#5]

Hi,

I have the following error : " from pyspark import SparkConf,SparkContext ImportError: No module named 'pyspark'"

Could you please help me with this error?

Thanks

[#6]

Will it work for spark version 2.3.0 ?

Could you please update it as per this version.